Dryrun pictures
Ernesto
February 25, 2017
Weaknesses of the model
- No seasonality
- Homogeneous fleet
- One quota market for Sablefish
- Alternative fisheries not simulated
What’s the point?
- We have a model and we have some data
- We want:
- Calibrate
- Select
- Validate
- Analyse
Calibrate
- Only a few free parameters
- Catchability per species
- Average hold size
- Behavioural Parameters
- We want to change them such that model is as close as possible to real data
Calibration procedure
- Force agents to go where logbook says they went
- Fit catchabilities and hold size so that simulated data looks like real data
- Now fix catchabilities and vary behavioural parameters
- Pick behavioural parameters that minimize distance to logbook data
- Check fully calibrated model against aggregate data again
Step 2

Step 5 - heatmapper

Select
- We have many options for heuristics
- Bandit agents
- Imitative agents
- Heatmap agents
- Which heuristic is best?
- Rank them by quality of fit back to aggregate data
Rank
## # A tibble: 9 × 2
## name error
## <chr> <dbl>
## 1 annealing 167.82941
## 2 bandit 17.47207
## 3 clamped 17.03515
## 4 eei 16.98512
## 5 eei2 16.94044
## 6 intercepts 11.54279
## 7 kernel 13.79445
## 8 perfect 18.59034
## 9 random 32.21017

Validate
- Look at other indicators that were not calibrated against
- Do they look okay?
Quota Price - Sablefish

Profits

Active fishers

Active Fishers

Profits
